Final Project
Adam Guenoun, Indira Martinez, Nicholas Solis
Introduction:
Within this analysis, we’ll investigate factors correlated to
diabetes. With a data set of 100,000 people, this investigation allows
us to display relations between ages, HbA1c levels, smoking history, and
glucose levels. With a wide range of data points, we begin to question
if there are trends within this data that match our general
understanding of diabetes. Our goal is to asses which of the 9 variables
play a stronger role to the development of diabetes and if we can prove
trends to better support our assumptions of this data. Through data
visualization, chart analysis, and numerical analysis we will be able to
present this data to convicne a general audience of the important
factors that contribute to diabteic trends.
library(tidyverse) ## Loaded for dplyr
library(ggplot2) ## Loaded for plotting
library(plotly) ## Loaded for interactive plots
library(readr) ## Loaded to read in data
library(knitr) ## Loaded to compute and display data
library(scales) ## Loaded to scale data
Male vs. Female
Blood Sugar Levels (HbA1c) Plot
For this part we will focus only on the HbA1c levels for males and
females.
- Slightly higher diabetes rates among males by a count of 2,876.
- More females fall into the normal blood sugar category compared to
males by a count of 7,134.
- Prediabetes in both genders are nearly identical , which suggests
that prediabetes affect both genders at nearly the same rate.
Overall, blood sugar regulation patterns appear balanced between both
genders.
99,982 x 4 (first 5 rows)
| Female |
0 |
6.6 |
Diabetic ≥ 6.5% |
| Female |
0 |
6.6 |
Diabetic ≥ 6.5% |
| Male |
0 |
5.7 |
Prediabetic 5.7% - 6.4% |
| Female |
0 |
5.0 |
Normal < 5.7% |
| Male |
0 |
4.8 |
Normal < 5.7% |
6 x 4 (first 5 rows)
| Female |
Diabetic ≥ 6.5% |
11835 |
20.21280 |
| Female |
Normal < 5.7% |
22492 |
38.41372 |
| Female |
Prediabetic 5.7% - 6.4% |
24225 |
41.37348 |
| Male |
Diabetic ≥ 6.5% |
8959 |
21.62443 |
| Male |
Normal < 5.7% |
15358 |
37.06976 |
BMI Distribution
by Hypertension Status Plot
Shows the distribution of BMI values based on hypertension status. A
violin plot is great for visualizing the distribution and density of BMI
across hypertension categories,
Shape and width: The width of each “violin” represents the density of
BMI values at different levels. Wider sections mean more individuals
have that BMI, while narrower sections indicate fewer people at those
values.
Comparison of distributions: The blue violin represents people
without hypertension (hypertension = 0), while the red violin represents
those with hypertension (hypertension = 1). By comparing them, you can
see how BMI differs between these groups.
The horizontal line around 25 BMI: This marks the median BMI for each
group. Since both violins have a horizontal line in roughly the same
position, it suggests that the median BMI is around 25 for both
hypertensive and non-hypertensive individuals.
Density trends: If the violins have different thicknesses in certain
BMI ranges, it tells you which BMI values are more or less common in
each group. People with hypertension seem to have a higher BMI overall,
but both groups share a similar median.
The distribution shape is different—for example, if one violin is
wider at higher BMI values, it suggests that hypertension is more common
among individuals with higher BMI.
Outliers or extreme values might appear as small bulges or extended
tails at the ends of the violins, showing individuals with very high or
low BMI.
10,000 x 9 (first 5 rows)
| Female |
80 |
0 |
1 |
never |
25.19 |
6.6 |
140 |
0 |
| Female |
54 |
0 |
0 |
No Info |
27.32 |
6.6 |
80 |
0 |
| Male |
28 |
0 |
0 |
never |
27.32 |
5.7 |
158 |
0 |
| Female |
36 |
0 |
0 |
current |
23.45 |
5.0 |
155 |
0 |
| Male |
76 |
1 |
1 |
current |
20.14 |
4.8 |
155 |
0 |
The graph below is separated by whether or not a person has
hypertension. With the comparison of BMI as the range, it’s seen that
majority of people with and without hypertension lie within a BMI range
of 25-29. Notice that for people with hypertension, the desnity
population above the red line is greater than that of people without
hypertension; indicating that there’s a larger of population of people
with hypertension that have a larger BMI
A relation to BMI and Heart
Disease
Each person within this scale has heart disease. Here a comparison is
made between declared underweight and overweight people, grouped by sex,
based on a BMI scale. There’s a significant increase in population
percentage for those who are considered overweight and that have heart
disease. With visual aid, it can be concluded that as weight increases,
chances of heart disease will increase.
An excpetion?
The data here is heavily dependent on BMI scale. It is important to
note that BMI is not really a great determination for those who have
diabetes, but there is a general trend within the data that people who
have a BMI over 30 are more likely to be diabetic.
